SUTD Visual Computing Group
Our group focuses on machine learning and computer vision research. We are part of Singapore University of Technology and Design.
Singapore
Pinned Repositories
awesome-generative-modeling-under-data-constraints
A Comprehensive List of Works for Generative Modeling with Limited Data, Few Shots, and Zero Shot
dag-gans
Data Augmentation optimized for GAN
Fourier-Discrepancies-CNN-Detection
[CVPR 2021: Oral] In this work, we show that high frequency Fourier spectrum decay discrepancies are not inherent characteristics for existing CNN-based generative models.
google-streetview-gis-stack
This tool helps to generate Google Street View coverage maps by leveraging on Geographic Information System and Google Static Street View API
KML-Classification
[NeurIPS 2021] Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning | PyTorch Implementation
label-smoothing-multi-label-classification
Label Smoothing Experiment for Multi-label classification using Pascal VOC 2012 dataset
LS-KD-compatibility
[ICML 2022] This work investigates the compatibility between label smoothing (LS) and knowledge distillation (KD). We suggest to use an LS-trained teacher with a low-temperature transfer to render high performance students.
Re-thinking_MI
[CVPR-2023] Re-thinking Model Inversion Attacks Against Deep Neural Networks
tokyo_24-7_image_retrieval_annotations
Annotated subset of Tokyo 24/7 Google Street View Dataset for Visual Geo-localization research. It consists of 16,000 dataset images and 49 distinct query locations taken at day/ evening/ night for a total of 147 query images.
transferable-forensic-features
[ECCV 2022: Oral] In this work, we discover that color is a crtical transferable forensic feature (T-FF) in universal detectors for detecting CNN-generated images.
SUTD Visual Computing Group's Repositories
sutd-visual-computing-group/dag-gans
Data Augmentation optimized for GAN
sutd-visual-computing-group/Re-thinking_MI
[CVPR-2023] Re-thinking Model Inversion Attacks Against Deep Neural Networks
sutd-visual-computing-group/Fourier-Discrepancies-CNN-Detection
[CVPR 2021: Oral] In this work, we show that high frequency Fourier spectrum decay discrepancies are not inherent characteristics for existing CNN-based generative models.
sutd-visual-computing-group/awesome-generative-modeling-under-data-constraints
A Comprehensive List of Works for Generative Modeling with Limited Data, Few Shots, and Zero Shot
sutd-visual-computing-group/transferable-forensic-features
[ECCV 2022: Oral] In this work, we discover that color is a crtical transferable forensic feature (T-FF) in universal detectors for detecting CNN-generated images.
sutd-visual-computing-group/LS-KD-compatibility
[ICML 2022] This work investigates the compatibility between label smoothing (LS) and knowledge distillation (KD). We suggest to use an LS-trained teacher with a low-temperature transfer to render high performance students.
sutd-visual-computing-group/KML-Classification
[NeurIPS 2021] Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning | PyTorch Implementation
sutd-visual-computing-group/tokyo_24-7_image_retrieval_annotations
Annotated subset of Tokyo 24/7 Google Street View Dataset for Visual Geo-localization research. It consists of 16,000 dataset images and 49 distinct query locations taken at day/ evening/ night for a total of 147 query images.
sutd-visual-computing-group/google-streetview-gis-stack
This tool helps to generate Google Street View coverage maps by leveraging on Geographic Information System and Google Static Street View API
sutd-visual-computing-group/label-smoothing-multi-label-classification
Label Smoothing Experiment for Multi-label classification using Pascal VOC 2012 dataset
sutd-visual-computing-group/research-reproducibility-guide-book
This Guide book is written with the intention of helping researchers and engineers working in machine learning domains to publish reproducible research.
sutd-visual-computing-group/FairTL
sutd-visual-computing-group/multimodal-fisher-vector
[ICASSP 2016] Dataset for egocentric activity recognition : "Egocentric Activity Recognition with Multimodal Fisher Vector"
sutd-visual-computing-group/sutd-visual-computing-group.github.io
sutd-visual-computing-group/AdAM
sutd-visual-computing-group/CLEAM
sutd-visual-computing-group/FairQueue